diff --git a/configs/cyclegan_horse2zebra.yaml b/configs/cyclegan_horse2zebra.yaml
index f5c80547d60ea8949b30b8c3bb49d359c7ca3f5b..e0b0c294d91108a1207bae11540b3fef2c48e6dc 100644
--- a/configs/cyclegan_horse2zebra.yaml
+++ b/configs/cyclegan_horse2zebra.yaml
@@ -120,6 +120,11 @@ log_config:
 snapshot_config:
   interval: 5
 
-export_model:
-  - {name: 'netG_A', inputs_num: 1}
-  - {name: 'netG_B', inputs_num: 1}
+validate:
+  interval: 30000
+  save_img: false
+  metrics:
+    fid: # metric name, can be arbitrary
+        name: FID
+        batch_size: 8
+
diff --git a/ppgan/models/cycle_gan_model.py b/ppgan/models/cycle_gan_model.py
index 6d1c3f0950b96dc9588ab598a572cc9497c302d3..000938eaa3042eaa7e9a8a6cb3ac48bb6f131cef 100644
--- a/ppgan/models/cycle_gan_model.py
+++ b/ppgan/models/cycle_gan_model.py
@@ -242,3 +242,13 @@ class CycleGANModel(BaseModel):
         self.backward_D_B()
         # update D_A and D_B's weights
         optimizers['optimD'].step()
+
+
+    def test_iter(self, metrics=None):
+        self.nets['netG_A'].eval()
+        self.forward()
+        with paddle.no_grad():
+            if metrics is not None:
+                for metric in metrics.values():
+                    metric.update(self.fake_B, self.real_B)
+        self.nets['netG_A'].train()
diff --git a/test_tipc/configs/msvsr/train_infer_python.txt b/test_tipc/configs/msvsr/train_infer_python.txt
index a8480370217c190fbb0a3dfd9fd808fd775a6959..0f393abe98f5a1bc5b5e53f104be2c3e4e214fd2 100644
--- a/test_tipc/configs/msvsr/train_infer_python.txt
+++ b/test_tipc/configs/msvsr/train_infer_python.txt
@@ -13,7 +13,7 @@ train_infer_img_dir:./data/msvsr_reds/test
 null:null
 ##
 trainer:norm_train
-norm_train:tools/main.py -c configs/msvsr_reds.yaml --seed 123 -o dataset.train.dataset.num_clips=2 dataset.train.num_workers=0 log_config.interval=1 snapshot_config.interval=5 
+norm_train:tools/main.py -c configs/msvsr_reds.yaml --seed 123 -o dataset.train.dataset.num_clips=2 dataset.train.num_workers=0 log_config.interval=1 snapshot_config.interval=5 dataset.train.dataset.number_frames=2 
 pact_train:null
 fpgm_train:null
 distill_train:null
@@ -27,7 +27,7 @@ null:null
 ===========================infer_params===========================
 --output_dir:./output/
 load:null
-norm_export:tools/export_model.py -c configs/msvsr_reds.yaml  --inputs_size="1,4,3,180,320" --load 
+norm_export:tools/export_model.py -c configs/msvsr_reds.yaml  --inputs_size="1,2,3,180,320" --load 
 quant_export:null 
 fpgm_export:null
 distill_export:null
@@ -37,7 +37,7 @@ inference_dir:multistagevsrmodel_generator
 train_model:./inference/msvsr/multistagevsrmodel_generator
 infer_export:null
 infer_quant:False
-inference:tools/inference.py --model_type msvsr -c configs/msvsr_reds.yaml --seed 123 -o dataset.test.num_clips=2 dataset.test.number_frames=4 --output_path test_tipc/output/
+inference:tools/inference.py --model_type msvsr -c configs/msvsr_reds.yaml --seed 123 -o dataset.test.num_clips=2 dataset.test.number_frames=2 --output_path test_tipc/output/
 --device:gpu
 null:null
 null:null
@@ -48,4 +48,4 @@ null:null
 null:null
 null:null
 --benchmark:True
-null:null
\ No newline at end of file
+null:null
diff --git a/test_tipc/results/python_msvsr_results_fp32.txt b/test_tipc/results/python_msvsr_results_fp32.txt
index 0de2d2f94fc4912bc2d404487351c63f46478fd4..1462d709b7bf9fdf62504a7789cc9965e8fe8fa6 100644
--- a/test_tipc/results/python_msvsr_results_fp32.txt
+++ b/test_tipc/results/python_msvsr_results_fp32.txt
@@ -1,2 +1,2 @@
-Metric psnr: 27.3670
-Metric ssim: 0.8021
\ No newline at end of file
+Metric psnr: 24.3250
+Metric ssim: 0.6497
\ No newline at end of file